1. Technical Field
The present invention relates to a method of resource control for use within a wireless network, and in particular to a method of resource control wherein congestion pricing is used to determine resource allocation between multiple users.
2. Related Art
Procedures for efficient control and management of wireless network resources are becoming increasingly important. This is due to two factors: First, there is a limited ability, compared to fixed wire-line networks, for increasing the capacity of mobile wireless networks. Second, emerging multimedia services and applications will increase the demand for bandwidth in wireless networks.
Congestion pricing has been identified as a flexible mechanism for efficient and robust resource control in fixed wire-line networks, as discussed by F. P. Kelly in Charging and rate control for elastic traffic, European Transactions on Telecommunications, vol. 8 pp. 33-37 January 1997. Congestion pricing has also already been considered for wireless networks, as will become apparent from the following discussion of the prior art in the field.
The authors of Goodman et al. Power control for wireless data IEEE personal Comm. 7:48-54, April 2000 consider a utility which is interpreted as the number of information bits transmitted per unit of energy. The utility has the property that for a bit-energy-to-noise-density ratio Eb/No larger than some value, the utility decreases with the increase of Eb/No. It is shown that for the non-cooperative game where mobile users adjust their power to maximize their utility, there exists a unique Nash equilibrium. In the equilibrium all users achieve the same bit-energy-to-noise-density ratio Eb/No. Moreover, the latter satisfies the same equation as the one that the optimal target bit-energy-to-noise-density ratio that maximizes the net utility in our framework satisfies.
Xiao et al. Utility-based power control in cellular wireless systems Proc of IEEE INFOCOM'01 Anchorage Ak. April 2001 consider a utility, having a sigmoid shape, that is a function of the bit-energy-to-noise-density ratio, and formulate a utility-based distributed power control algorithm where each user seeks the maximize his net utility, i.e., the difference between his utility minus the cost of power, which is taken to be a linear function of the power. The authors indicate that price adjustment can be used to control resource usage, without however relating this to constraints on the wireless resources. They propose a function where prices are proportional to the interference a mobile host experiences, hence the price per unit of power can be different for different mobile hosts. The work considers only the downlink, indicating that the uplink could be handled similarly. If, however, in the uplink the transmit power is charged, this does not discourage mobile hosts from declaring a power different from their true power or not update the price per unit of power according to the above.
The authors of Liu et al, Forward-Link CDMA resource allocation based on pricing, IEEE Wireless Communications and Networking conference (WCNC), 2000, consider downlink resource allocation in CDMA networks based on pricing. The user utility is a step function of the bit-energy-to-noise-density ratio, and the price each mobile is charged with contains a constant term (price per code) and a term linear in the transmitted power from the base station. It is also assumed that each base station is charged by some amount that is proportional to the total power with which it is transmitting; this charge accounts for the interference it is causing to neighbouring cells. They then go on to investigate the problem of maximizing the total utility minus the base station's power charge and of the total revenue (payment received from mobile hosts) minus the base station's power charge.
The authors of Ji et al, Non-cooperative uplink power control in cellular radio systems Acm/Baltzer Wireless Networks Journal Vol 4. pp 233-240, 1998 consider a utility that is a monotonically increasing concave function of the bit-energy-to-noise-density ratio and a monotonically decreasing concave function of the mobile host (transmitter) power. Each mobile adjusts its sending power (the rate is considered fixed) so as to maximize its utility. Under some assumption regarding the utility, a Nash (non-cooperative) equilibrium exists.
The work in Lu et al, Integrating power control, error correction coding and scheduling for a CDMA downlink system IEEE J. Select. Areas Commun. 17(5):978-989, June 1999 discusses in a qualitative manner the concept of utility, specifically as a function of bandwidth and bit error rate, at various levels of CDMA system (user, individual cell, and whole system).
The authors of Elaoud et al. Adaptive Allocation of CDMA resources for network level QoS assurances, ACM/IEEE International Conference on Mobile Computing and Networking (MOBICOM) pp 191-199, 2000 consider a cost function with two components, one linear in the transmitted power and the other linear in the target Eb/No. Using this cost function they formulate problems that take into account the deadline requirements of each packet, and adapt the target Eb/No based on these deadlines; it is assumed that the network-level QoS requirements translate to such deadline requirements.
Another line of research has considered the problem of maximizing the aggregate throughput in CDMA systems. The work in Sampath et al, Power control and resource management for a multimedia CDMA wireless system, Proc of IEEE Int Symp Personal, Indoor, Mobile Radio Commun (PIMRC), Toronto, Canada, 1995 considers the problems of minimizing the aggregate power and of maximizing the sum of rates, given target Eb/No values and constraints on the maximum power and minimum rate. Moreover, the authors of Ramakrishna et al, A scheme for throughput maximisation in a dual class CDMA system IEEE J. Select Areas Commun, 16(6):830-844, August 1998, show that in hybrid CDMA/TDMA systems supporting real-time (delay intolerant) and non real-time (delay tolerant) traffic, both with fixed target Eb/No values, the sum of rates of the non real-time traffic is maximized if it is scheduled so that only one non real-time source sends traffic in each time slot.
Whereas the previous work considered fixed Eb/No values, Honig et al, Allocation of DS-CDMA parameters to achieve multiple rates and qualities of service IEEE Trans on Vehicular Technology 49(2):506-519, March 2000 and Oh et al Dynamic Spreading gain in multiservice CDMA networks IEEE J. Select. Areas Commun. 17(5):918-927 May 1999, both consider the case where both target Eb/No and the rate (equivalently, the spreading gain) can be controlled. More particularly, Honig et al considers a system with two classes, for data and voice, and investigates the problem of assigning powers processing gains to each class in order to optimise performance in terms of average delay for data and bit error rate for voice; it is assumed that traffic for both types follows a Poisson process. Oh et al. investigates the maximization of throughput (taking into account losses in the wireless network) and shows that the optimal spreading gain is inversely proportional to the multiple access interference and that the optimal retransmission probability for data traffic is one.
Although many of these references use the concept of utility to optimise sending rate over a wireless link, none consider a framework that seamlessly encompasses all network resources (wireless spectrum, base station power, mobile station battery, as well as fixed network resources), and also none consider any of the engineering to realise this. The essential distinction is between a theoretical utility function and a practical QoS buying policy to implement it.
Further work on engineering of congestion control for wireless networks can be found in Montenegro et al, “Long thin networks” RFC2757 (January 2000), http://www.ietf.org/rfc/rfc2757.txt, Inamura et al, “TCP over 2.5G and 3G wireless networks”, (February 2001), http://search.ietf.org/internet-drafts/draft-ietf-pilc-2.5g3g-03.txt, and from the Uni of Bejing/Nokia, such as “A proposal to apply ECN into Wireless and Mobile Networks”, Jian Ma, Fei Peng (Sep. 17, 2001), http://www.ietf.org/internet-drafts/draft-fpengy-ecn-04.txt. The latter document in particular suggests distinguishing congestion from loss using explicit congestion notification (ECN) instead of packet drop.
As will be apparent from the review of the prior art given above, the vast majority of prior work that consider the application of microeconomic approaches to resource control in wireless networks have focused exclusively on the cost of battery power. This was motivated by the fact that battery power was, and continues to be, a scarce resource in mobile hosts. In future 3G wireless networks supporting multimedia services with high bandwidth requirements, however, wireless resources are also likely be scarce, hence in addition to the cost of battery power, it will be necessary to incorporate the congestion of wireless resources in power and rate control procedures.
Moreover, the widespread use of the Internet necessitates the seamless interworking of protocols and procedures in mobile wireless networks, with those in fixed IP-based networks. One important procedure is congestion control, which in IP networks is performed mainly by TCP (Transmission Control Protocol). There is therefore also the need to provide for seamless congestion control signalling, which seamlessly integrates a wireless network with that of any fixed network over which the wireless network's data traffic may also have to flow.